Q-omics provides the consensus-scored WIPI2 profile across patient tissues and cancer cell-line models. WIPI2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, WIPI2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, WIPI2 protein abundance shows 18,679 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where WIPI2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for WIPI2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WIPI2 survival associations across molecular data types. WIPI2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WIPI2 RNA expression–survival associations across cancer types. High WIPI2 expression shows unfavorable associations in HNSC, ACC, BLCA and COAD, but favorable associations in SCLC and PAAD. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify HNSC as the clearest survival context for WIPI2 RNA expression.
This table summarizes WIPI2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for WIPI2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WIPI2 shows higher tumor expression in HNSC, KIRP, COAD, LUAD, LIHC and KICH. The HNSC box plot shows higher WIPI2 RNA expression in tumor versus normal tissue (log2 FC = +0.616, t-test p < 0.001).
This table shows molecular features associated with WIPI2 in patient tissues and cancer cell lines. In patient samples, WIPI2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, WIPI2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
